Status:

UNKNOWN

Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology

Lead Sponsor:

Jinsong Wu

Conditions:

Central Nervous System Neoplasms

Eligibility:

All Genders

18+ years

Phase:

NA

Brief Summary

This is a multi-center, prospective, self-controlled, diagnostic accuracy comparative study of Artificial Intelligence Diagnostic System for Surgical Neuropathology. The investigators will compare the...

Detailed Description

In this study, 141 patients will be recruited. After being enrolled, the patients will accept surgery and specimens for pathological analysis will be taken according to the routine treatment process. ...

Eligibility Criteria

Inclusion

  • Patients or their guardians understand the research process, agree to use their data, and sign the informed consent form;
  • Aged \>=18 years;
  • MRI shows intracranial spaceoccupying lesions;
  • The clinical diagnosis is glioma, metastasis or lymphoma thus requiring surgical treatment;
  • The patient is willing to accept the surgery.

Exclusion

  • The patient has serious underlying diseases thus is not suitable for surgery;
  • After further clinical evaluation, surgical treatment was not the best choice;
  • The patient participate in clinical research of other drugs or devices;
  • The researchers believe that there are other factors that will make the patients unable to complete the study.

Key Trial Info

Start Date :

February 1 2021

Trial Type :

INTERVENTIONAL

Allocation :

ESTIMATED

End Date :

February 1 2022

Estimated Enrollment :

141 Patients enrolled

Trial Details

Trial ID

NCT04671368

Start Date

February 1 2021

End Date

February 1 2022

Last Update

December 17 2020

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Diagnostic Efficiency of Artificial Intelligence for Surgical Neuropathology | DecenTrialz